Nasib Marbun, Shahnoza Khaydaraliyevna Pozilova, H. Shahadi, Ankush Ghosh
{"title":"搜索引擎优化专家招聘中偏好选择指数的应用","authors":"Nasib Marbun, Shahnoza Khaydaraliyevna Pozilova, H. Shahadi, Ankush Ghosh","doi":"10.58905/saga.v1i4.241","DOIUrl":null,"url":null,"abstract":"Search Engine Optimization Specialist is one of the important factors that can help digital agencies improve services to all their customers. This research aims to develop a decision-making system in the recruitment process of Search Engine Optimization Specialists by applying the Preference Selection Index method. The Search Engine Optimization Specialist recruitment decision-making system in this study uses 5 (five) criteria, namely educational background, ability to use SEO tools, work experience as a Search Engine Optimization Specialist, digital marketing skills, and age. The research sample data collection technique related to the recruitment of Search Engine Optimization Specialists used in this research is Literature Study. After the author succeeds in collecting research sample data, at the next stage the author analyzes the application of the Preference Selection Index method in the recruitment of Search Engine Optimization Specialists. The results of this study show that alternative A02 (0.855641604) has the highest value and gets the first ranking position. Meanwhile, the alternatives that get the second to fifth ranking positions are A05 (0,834620739), A03 (0,741086734), A04 (0,716537597), and A01 (0,708920064). So that the most recommended alternative based on the calculation of the Preference Selection Index on the recruitment of Search Engine Optimization Specialists in this study is alternative A02 (0,855641604).","PeriodicalId":176651,"journal":{"name":"SAGA: Journal of Technology and Information System","volume":"62 45","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of Preference Selection Index in Recruitment of Search Engine Optimization Specialist\",\"authors\":\"Nasib Marbun, Shahnoza Khaydaraliyevna Pozilova, H. Shahadi, Ankush Ghosh\",\"doi\":\"10.58905/saga.v1i4.241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Search Engine Optimization Specialist is one of the important factors that can help digital agencies improve services to all their customers. This research aims to develop a decision-making system in the recruitment process of Search Engine Optimization Specialists by applying the Preference Selection Index method. The Search Engine Optimization Specialist recruitment decision-making system in this study uses 5 (five) criteria, namely educational background, ability to use SEO tools, work experience as a Search Engine Optimization Specialist, digital marketing skills, and age. The research sample data collection technique related to the recruitment of Search Engine Optimization Specialists used in this research is Literature Study. After the author succeeds in collecting research sample data, at the next stage the author analyzes the application of the Preference Selection Index method in the recruitment of Search Engine Optimization Specialists. The results of this study show that alternative A02 (0.855641604) has the highest value and gets the first ranking position. Meanwhile, the alternatives that get the second to fifth ranking positions are A05 (0,834620739), A03 (0,741086734), A04 (0,716537597), and A01 (0,708920064). So that the most recommended alternative based on the calculation of the Preference Selection Index on the recruitment of Search Engine Optimization Specialists in this study is alternative A02 (0,855641604).\",\"PeriodicalId\":176651,\"journal\":{\"name\":\"SAGA: Journal of Technology and Information System\",\"volume\":\"62 45\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SAGA: Journal of Technology and Information System\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.58905/saga.v1i4.241\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SAGA: Journal of Technology and Information System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.58905/saga.v1i4.241","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Preference Selection Index in Recruitment of Search Engine Optimization Specialist
Search Engine Optimization Specialist is one of the important factors that can help digital agencies improve services to all their customers. This research aims to develop a decision-making system in the recruitment process of Search Engine Optimization Specialists by applying the Preference Selection Index method. The Search Engine Optimization Specialist recruitment decision-making system in this study uses 5 (five) criteria, namely educational background, ability to use SEO tools, work experience as a Search Engine Optimization Specialist, digital marketing skills, and age. The research sample data collection technique related to the recruitment of Search Engine Optimization Specialists used in this research is Literature Study. After the author succeeds in collecting research sample data, at the next stage the author analyzes the application of the Preference Selection Index method in the recruitment of Search Engine Optimization Specialists. The results of this study show that alternative A02 (0.855641604) has the highest value and gets the first ranking position. Meanwhile, the alternatives that get the second to fifth ranking positions are A05 (0,834620739), A03 (0,741086734), A04 (0,716537597), and A01 (0,708920064). So that the most recommended alternative based on the calculation of the Preference Selection Index on the recruitment of Search Engine Optimization Specialists in this study is alternative A02 (0,855641604).